{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "timeseries.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/lmoroney/tfbook/blob/master/chapter9/timeseries.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zX4Kg8DUTKWO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "# https://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License."
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D1J15Vh_1Jih",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "04585cb4-eb9c-4c85-f14d-a71a492cade2"
      },
      "source": [
        "try:\n",
        "  # %tensorflow_version only exists in Colab.\n",
        "  %tensorflow_version 2.x\n",
        "except Exception:\n",
        "  pass\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "TensorFlow 2.x selected.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BOjujz601HcS",
        "colab_type": "code",
        "outputId": "08b0563e-5737-43f8-ec07-2ff423928635",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "print(tf.__version__)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2.1.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "Zswl7jRtGzkk",
        "colab": {}
      },
      "source": [
        "def plot_series(time, series, format=\"-\", start=0, end=None):\n",
        "    plt.plot(time[start:end], series[start:end], format)\n",
        "    plt.xlabel(\"Time\")\n",
        "    plt.ylabel(\"Value\")\n",
        "    plt.grid(True)\n",
        "\n",
        "def trend(time, slope=0):\n",
        "    return slope * time\n",
        "\n",
        "def seasonal_pattern(season_time):\n",
        "    \"\"\"Just an arbitrary pattern, you can change it if you wish\"\"\"\n",
        "    return np.where(season_time < 0.4,\n",
        "                    np.cos(season_time * 2 * np.pi),\n",
        "                    1 / np.exp(3 * season_time))\n",
        "\n",
        "def seasonality(time, period, amplitude=1, phase=0):\n",
        "    \"\"\"Repeats the same pattern at each period\"\"\"\n",
        "    season_time = ((time + phase) % period) / period\n",
        "    return amplitude * seasonal_pattern(season_time)\n",
        "\n",
        "def noise(time, noise_level=1, seed=None):\n",
        "    rnd = np.random.RandomState(seed)\n",
        "    return rnd.randn(len(time)) * noise_level\n",
        "\n",
        "time = np.arange(4 * 365 + 1, dtype=\"float32\")\n",
        "baseline = 10\n",
        "series = trend(time, 0.1)  \n",
        "baseline = 10\n",
        "amplitude = 20\n",
        "slope = 0.09\n",
        "noise_level = 5\n",
        "\n",
        "# Create the series\n",
        "series = baseline + trend(time, slope) + seasonality(time, period=365, amplitude=amplitude)\n",
        "# Update with noise\n",
        "series += noise(time, noise_level, seed=42)\n",
        "\n",
        "split_time = 1000\n",
        "time_train = time[:split_time]\n",
        "x_train = series[:split_time]\n",
        "time_valid = time[split_time:]\n",
        "x_valid = series[split_time:]\n",
        "\n",
        "window_size = 20\n",
        "batch_size = 32\n",
        "shuffle_buffer_size = 1000"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tVH2XEt4yA4m",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "outputId": "7f991893-33a0-4ca5-e58f-d61cc8cf9605"
      },
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "plot_series(time_valid, x_valid)\n"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KC1eyVASZIvIiuyyVUL/puBiZqWA8Nkop7EMWXdfTR8bxnjufwpZVLXj4D2+Tp6uC8qbP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\nSSOzIJMkSRqZBZkkSdLI/g0w5TLPzfab1QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4sTTIOCbyShY",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def windowed_dataset(series, window_size, batch_size, shuffle_buffer):\n",
        "  dataset = tf.data.Dataset.from_tensor_slices(series)\n",
        "  dataset = dataset.window(window_size + 1, shift=1, drop_remainder=True)\n",
        "  dataset = dataset.flat_map(lambda window: window.batch(window_size + 1))\n",
        "  dataset = dataset.shuffle(shuffle_buffer).map(lambda window: (window[:-1], window[-1]))\n",
        "  dataset = dataset.batch(batch_size).prefetch(1)\n",
        "  return dataset"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TW-vT7eLYAdb",
        "colab_type": "code",
        "outputId": "0f941a0d-5db5-4ecf-8f24-4f5f97a0965d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "dataset = windowed_dataset(x_train, window_size, batch_size, shuffle_buffer_size)\n",
        "\n",
        "\n",
        "model = tf.keras.models.Sequential([\n",
        "    tf.keras.layers.Dense(10, input_shape=[window_size], activation=\"relu\"), \n",
        "    tf.keras.layers.Dense(10, activation=\"relu\"), \n",
        "    tf.keras.layers.Dense(1)\n",
        "])\n",
        "\n",
        "model.compile(loss=\"mse\", optimizer=tf.keras.optimizers.SGD(lr=1e-6, momentum=0.9))\n",
        "model.fit(dataset,epochs=100,verbose=0)\n",
        "\n"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7f421d549128>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "efhco2rYyIFF",
        "colab_type": "code",
        "outputId": "e2df31ab-20e8-498a-f99c-1c61491a146f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        }
      },
      "source": [
        "forecast = []\n",
        "for time in range(len(series) - window_size):\n",
        "  forecast.append(model.predict(series[time:time + window_size][np.newaxis]))\n",
        "\n",
        "forecast = forecast[split_time-window_size:]\n",
        "results = np.array(forecast)[:, 0, 0]\n",
        "\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "\n",
        "plot_series(time_valid, x_valid)\n",
        "plot_series(time_valid, results)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ZSGbJPXk7O/LnYgcu3vDoGJ2dnWzbV6Ah6dHZ2clYSbOUIcaP9AFLaWaC37Ce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\nYII=\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-kT6j186YO6K",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tf.keras.metrics.mean_absolute_error(x_valid, results).numpy()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tnCe_nBKu7RB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dataset = windowed_dataset(x_train, window_size, batch_size, shuffle_buffer_size)\n",
        "\n",
        "\n",
        "model = tf.keras.models.Sequential([\n",
        "    tf.keras.layers.Dense(10, input_shape=[window_size], activation=\"relu\"), \n",
        "    tf.keras.layers.Dense(10, activation=\"relu\"), \n",
        "    tf.keras.layers.Dense(1)\n",
        "])\n",
        "\n",
        "lr_schedule = tf.keras.callbacks.LearningRateScheduler(\n",
        "    lambda epoch: 1e-8 * 10**(epoch / 20))\n",
        "optimizer = tf.keras.optimizers.SGD(lr=1e-8, momentum=0.9)\n",
        "model.compile(loss=\"mse\", optimizer=optimizer)\n",
        "history = model.fit(dataset, epochs=100, callbacks=[lr_schedule], verbose=0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ZaNsM2IgCd_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "lrs = 1e-8 * (10 ** (np.arange(100) / 20))\n",
        "plt.semilogx(lrs, history.history[\"loss\"])\n",
        "plt.axis([1e-8, 1e-3, 0, 300])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QDwW0Q7ovYK1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "window_size = 30\n",
        "dataset = windowed_dataset(x_train, window_size, batch_size, shuffle_buffer_size)\n",
        "\n",
        "model = tf.keras.models.Sequential([\n",
        "  tf.keras.layers.Dense(10, activation=\"relu\", input_shape=[window_size]),\n",
        "  tf.keras.layers.Dense(10, activation=\"relu\"),\n",
        "  tf.keras.layers.Dense(1)\n",
        "])\n",
        "\n",
        "optimizer = tf.keras.optimizers.SGD(lr=8e-6, momentum=0.9)\n",
        "model.compile(loss=\"mse\", optimizer=optimizer)\n",
        "history = model.fit(dataset, epochs=500, verbose=0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iXBMO1HM9AHX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "loss = history.history['loss']\n",
        "epochs = range(len(loss))\n",
        "plt.plot(epochs, loss, 'b', label='Training Loss')\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xakiRU7R7WAo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Plot all but the first 10\n",
        "loss = history.history['loss']\n",
        "epochs = range(10, len(loss))\n",
        "plot_loss = loss[10:]\n",
        "print(plot_loss)\n",
        "plt.plot(epochs, plot_loss, 'b', label='Training Loss')\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YUOPUeHWvvBG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "forecast = []\n",
        "for time in range(len(series) - window_size):\n",
        "  forecast.append(model.predict(series[time:time + window_size][np.newaxis]))\n",
        "\n",
        "forecast = forecast[split_time-window_size:]\n",
        "results = np.array(forecast)[:, 0, 0]\n",
        "\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "\n",
        "plot_series(time_valid, x_valid)\n",
        "plot_series(time_valid, results)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W-GPjL2wv0yc",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tf.keras.metrics.mean_absolute_error(x_valid, results).numpy()"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}
